Repositories tagged with "retinanet"
mmdetection
open-mmlab
โOpenMMLab Detection Toolbox and Benchmarkโ
pytorch-retinanet
yhenon
โPytorch implementation of RetinaNet object detection.โ
cv-papers
yizt
โ่ฎก็ฎๆบ่ง่ง็ธๅ ณ่ฎบๆๆด็ใ่ฎฐๅฝใๅไบซ; ๅ ๆฌๅพๅๅ็ฑปใ็ฎๆ ๆฃๆตใ่ง่ง่ท่ธช/็ฎๆ ่ท่ธชใไบบ่ธ่ฏๅซ/ไบบ่ธ้ช่ฏใOCR/ๅบๆฏๆๆฌๆฃๆตๅ่ฏๅซ็ญ้ขๅใๆฌข่ฟๅ ๆ,ๆฌข่ฟๆๆญฃ้่ฏฏ,ๅๆถไนๆๅพ ่ฝๅคๅ ฑๅๅไธ๏ผ๏ผ! ๆ็ปญๆดๆฐไธญ... ...โ
retinanet-examples
NVIDIA
โFast and accurate object detection with end-to-end GPU optimizationโ
Pedestron
hasanirtiza
โ[Pedestron] Generalizable Pedestrian Detection: The Elephant In The Room. @ CVPR2021โ
mmdetection-to-tensorrt
grimoire
โconvert mmdetection model to tensorrt, support fp16, int8, batch input, dynamic shape etc.โ
tensorRT
Syencil
โTensorRT-7 Network Lib ๅ ๆฌๅธธ็จ็ฎๆ ๆฃๆตใๅ ณ้ฎ็นๆฃๆตใไบบ่ธๆฃๆตใOCR็ญ ๅฏ่ฎญ็ป่ชๅทฑๆฐๆฎโ
deepstream_tao_apps
NVIDIA-AI-IOT
โSample apps to demonstrate how to deploy models trained with TAO on DeepStreamโ
SimpleAICV_pytorch_training_examples
zgcr
โSimpleAICV:pytorch training examples.โ
RetinaNet_Tensorflow_Rotation
DetectionTeamUCAS
โFocal Loss for Dense Rotation Object Detectionโ
RetinaNet
c0nn3r
โAn implementation of RetinaNet in PyTorch.โ
Retinanet-Pytorch
yatengLG
โRetinanet็ฎๆ ๆฃๆต็ฎๆณ(็ฎๅ,ๆไบ,ๆ็จ,ๅ จไธญๆๆณจ้,ๅๆบๅคๅก่ฎญ็ป,่ง้ขๆฃๆต)(based on pytorch,Simple, Clear, Mutil GPU)โ
pytorch-multi-class-focal-loss
AdeelH
โAn (unofficial) implementation of Focal Loss, as described in the RetinaNet paper, generalized to the multi-class case.โ
detect_steel_bar
spytensor
โCCFDF AI ๆฐ้ข็ญๅคง่ตโ
Feature-Selective-Anchor-Free-Module-for-Single-Shot-Object-Detection
hdjang
โA PyTorch Implementation of Feature Selective Anchor-Free Module for Single-Shot Object Detection (CVPR'19)โ
ObjectDetection
ChristianMarzahl
โSome experiments with object detection in PyTorchโ
kaggle-rsna
tatigabru
โDeep Learning for Automatic Pneumonia Detection, RSNA challengeโ
Mammo-CLIP
batmanlab
โ[MICCAI 2024, top 11%] Official Pytorch implementation of Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammographyโ